wkkm.c

多层权核k均值算法

	for (ii=0; ii<nbnd; ii++){
	  //kDist[s][from] = 0;
	  kDist[ii][from] = 0;
	  s = bndind[ii];
	  for (j=xadj[s]; j<xadj[s+1]; j++)
	    if (where[adjncy[j]] == from)
	      //kDist[s][from] += adjwgt[j]*1.0/w[s];
	      kDist[ii][from] += adjwgt[j]*1.0/w[s];
	}
	temp_q = squared_sum[from]/(1.0*sum[from]*sum[from]);
	
	//for (s=0; s<nvtxs; s++)
	for (ii=0; ii<nbnd; ii++)
	  kDist[ii][from] = temp_q - 2*kDist[ii][from]/sum[from];
        
	for (j=xadj[tempid]; j<xadj[tempid+1]; j++) 
	  if (where[adjncy[j]] == to)
	    squared_sum[to] += 2*adjwgt[j];

	//for (s=0; s<nvtxs; s++){
	for (ii=0; ii<nbnd; ii++){
	  //kDist[s][to] = 0;
	  kDist[ii][to] = 0;
	  s = bndind[ii];
	  for (j=xadj[s]; j<xadj[s+1]; j++)
	    if (where[adjncy[j]] == to)
	      //kDist[s][to] += adjwgt[j]*1.0/w[s];
	      kDist[ii][to] += adjwgt[j]*1.0/w[s];
	}
	temp_q = squared_sum[to]/(1.0*sum[to]*sum[to]);
	
	//for (s=0; s<nvtxs; s++)
	for (ii=0; ii<nbnd; ii++)
	  //kDist[s][to] = temp_q - 2*kDist[s][to]/sum[to];
	  kDist[ii][to] = temp_q - 2*kDist[ii][to]/sum[to];
      }
    }
  fidx = samin(actual_length, accum_change);
  if (accum_change[fidx] < -epsilon * obj){
    for (i= fidx+1; i<=actual_length; i++)
      where[chain[i-1].point] = chain[i-1].from;
    moves = fidx;
    change = accum_change[fidx];
  }
  else{
    for (i= 0; i<actual_length; i++)
      where[chain[i].point] = chain[i].from;
    moves = 0;
    change = 0;
  }

  free(sum); free(squared_sum);free(accum_change); free(chain); free(mark);
  
  //for (i= 0; i<nvtxs; i++)
  for (i= 0; i<nbnd; i++)
    free(kDist[i]);
  free(kDist);
  
  return moves;
}
*/

float onePoint_move(GraphType *graph, int nparts, idxtype *sum, idxtype *squared_sum, idxtype *w, idxtype *self_sim, int **linearTerm, int ii){
  
  int k, j, s, i, nbnd, temp, q1, q2, minchange_id, new_squared_sum1, new_squared_sum2, me, nedges, nvtxs;
  float tempchange, minchange, obj, cut;
  idxtype *xadj, *adjncy, *adjwgt, *where, *bndptr, *bndind;
  
  nedges = graph->nedges;
  nvtxs = graph->nvtxs;
  xadj = graph->xadj;
  adjncy = graph->adjncy;
  adjwgt = graph->adjwgt;
  where = graph->where;
  nbnd = graph->nbnd;
  bndind = graph->bndind;
  bndptr = graph->bndptr;

  s = bndind[ii];
  me= where[s];
  minchange_id = me;
  minchange = 0;
  new_squared_sum1=  new_squared_sum2= squared_sum[me];

  if (sum[me] > w[s]){ // if this cluster where j belongs is not a singleton
    float inv_sum1 = 1.0/sum[me], inv_sum2 = 1.0/(sum[me]-w[s]);
    
    for(k= 0; k<me; k++){
      q1 = squared_sum[me] - linearTerm[ii][me]*2 + self_sim[ii];
      q2 = squared_sum[k] + linearTerm[ii][k] *2 + self_sim[ii]; 
      if(sum[k] >0)
	tempchange = squared_sum[me]*inv_sum1 + squared_sum[k]*1.0/sum[k] - q1*inv_sum2- q2*1.0/(sum[k]+w[s]);
      else if(w[s]>0) // if sum[k] ==0 but w[s] >0
	tempchange = squared_sum[me]*inv_sum1 - q1*inv_sum2 - q2*1.0/(sum[k]+w[s]);
      else // if sum[k] == 0 and w[s] ==0
	tempchange = squared_sum[me]*inv_sum1 - q1*inv_sum2;
	  
      if(tempchange < minchange){
	minchange = tempchange; 
	minchange_id = k;  
	new_squared_sum1 = q1;
	new_squared_sum2 = q2;
      }
    }
    for(k= me+1; k<nparts; k++){
      q1 = squared_sum[me] - linearTerm[ii][me]*2 +self_sim[ii];
      q2 = squared_sum[k] + linearTerm[ii][k]*2 + self_sim[ii]; 
      if(sum[k] >0)
	tempchange = squared_sum[me]*inv_sum1 + squared_sum[k]*1.0/sum[k] - q1*inv_sum2- q2*1.0/(sum[k]+w[s]);
      else if(w[s]>0) // if sum[k] ==0 but w[s] >0
	tempchange = squared_sum[me]*inv_sum1 - q1*inv_sum2 - q2*1.0/(sum[k]+w[s]);
      else // if sum[k] == 0 and w[s] ==0
	tempchange = squared_sum[me]*inv_sum1 - q1*inv_sum2;
      
      if(tempchange < minchange){
	minchange = tempchange; 
	minchange_id = k; 
	new_squared_sum1 = q1;
	new_squared_sum2 = q2;
      }
    }
    if (minchange < 0){
      where[s] = minchange_id;
      sum[me] -=  w[s];
      sum[minchange_id] +=  w[s];
      /*
      for (ii = 0; ii<nbnd; ii++)
	for (j = 0; j<nparts; j++)
	  linearTerm[ii][j] = 0;
      */
      for (j=xadj[s]; j<xadj[s+1]; j++){
	int boundary, adj_temp;
	adj_temp = adjncy[j];
	boundary = bndptr[adj_temp];
	if(boundary >-1) {
	  //if (where[adj_temp] == me){
	  //linearTerm[ii][me] -= adjwgt[j];
	    linearTerm[boundary][me] -= adjwgt[j];
	    //}
	    //if (where[adj_temp] == minchange_id){
	    //linearTerm[ii][minchange_id] += adjwgt[j];
	    linearTerm[boundary][minchange_id] += adjwgt[j];
	    //}
	}
      }
      /*
      for (ii =0; ii<nbnd; ii++){
	i = bndind[ii];
	for (j=xadj[i]; j<xadj[i+1]; j++)
	  linearTerm[ii][where[adjncy[j]]] += adjwgt[j];
      }
      */
      
      
      squared_sum[me] = new_squared_sum1;
      squared_sum[minchange_id] = new_squared_sum2;
    }
  }
  return minchange;
}

void move1Point2EmptyCluster(GraphType *graph, int nparts, idxtype *sum, idxtype *squared_sum, idxtype *w, idxtype *self_sim, int **linearTerm, int k){
  int j, s, ii, nbnd, q1, q2, minchange_id, new_squared_sum1, new_squared_sum2, me, nvtxs;
  float tempchange, minchange;
  idxtype *xadj, *adjncy, *adjwgt, *where, *bndptr, *bndind;
  
  nvtxs = graph->nvtxs;
  xadj = graph->xadj;
  adjncy = graph->adjncy;
  adjwgt = graph->adjwgt;
  where = graph->where;
  nbnd = graph->nbnd;
  bndind = graph->bndind;
  bndptr = graph->bndptr;
  minchange_id = bndind[0];
  minchange = FLT_MAX;

  for(ii=0; ii<nbnd; ii++){
    s = bndind[ii];
    me= where[s];
    new_squared_sum1=  new_squared_sum2= squared_sum[me];
    
    if (sum[me] > w[s]){ // if this cluster where j belongs is not a singleton
      float inv_sum1 = 1.0/sum[me], inv_sum2 = 1.0/(sum[me]-w[s]);
      
      q1 = squared_sum[me] - linearTerm[ii][me]*2 + self_sim[ii];
      q2 = squared_sum[k] + linearTerm[ii][k] *2 + self_sim[ii]; 
      if(w[s]>0) // note that sum[k] ==0; if w[s] >0
	tempchange = squared_sum[me]*inv_sum1 - q1*inv_sum2 - q2*1.0/(sum[k]+w[s]);
      else // if sum[k] == 0 and w[s] ==0
	tempchange = squared_sum[me]*inv_sum1 - q1*inv_sum2;
      
      if(tempchange < minchange){
	minchange = tempchange; 
	minchange_id = s;  
	new_squared_sum1 = q1;
	new_squared_sum2 = q2;
      }
    }
  }
  
  where[minchange_id] = k;
  sum[me] -=  w[minchange_id];
  sum[k] +=  w[minchange_id];
  
  for (j=xadj[minchange_id]; j<xadj[minchange_id+1]; j++){
    int boundary, adj_temp;
    adj_temp = adjncy[j];
    boundary = bndptr[adj_temp];
    if(boundary >-1) {
      linearTerm[boundary][me] -= adjwgt[j];
      linearTerm[boundary][k] += adjwgt[j];
    }
    squared_sum[me] = new_squared_sum1;
    squared_sum[k] = new_squared_sum2;
  }
}

int local_search(CtrlType *ctrl, GraphType *graph, int nparts, int chain_length, idxtype *w, float *tpwgts, float ubfactor)
     //return # of points moved
{
  int nvtxs, nedges, nbnd, me, i, j, k, s, ii;
  idxtype *sum, *squared_sum, *xadj, *adjncy, *adjwgt, *where, *bndptr, *bndind, *self_sim;
  float change, obj, epsilon, accum_change, minchange;
  int moves, loopTimes, **linearTerm;

  nedges = graph->nedges;
  nvtxs = graph->nvtxs;
  xadj = graph->xadj;
  adjncy = graph->adjncy;
  adjwgt = graph->adjwgt;
  where = graph->where;
  nbnd = graph->nbnd;
  bndind = graph->bndind;
  bndptr = graph->bndptr;
  
  sum = idxsmalloc(nparts,0, "Local_search: weight sum");
  squared_sum = idxsmalloc(nparts,0,"Local_search: weight squared sum");
  self_sim = idxsmalloc(nbnd, 0, "Local_search: self similarity");
  linearTerm = i2malloc(nbnd, nparts, "Local_search: linear term");
  
  
  moves = 0;
  epsilon =.001;
  
  for (i=0; i<nvtxs; i++)
    sum[where[i]] += w[i]; 
  for (i=0; i<nvtxs; i++){
    me = where[i];
    for (j=xadj[i]; j<xadj[i+1]; j++) 
      if (where[adjncy[j]] == me)
	squared_sum[me] += adjwgt[j];
  }
  
  for (ii = 0; ii<nbnd; ii++)
    for (j = 0; j<nparts; j++)
      linearTerm[ii][j] = 0;
  for (ii =0; ii<nbnd; ii++){
    s = bndind[ii];
    for (j=xadj[s]; j<xadj[s+1]; j++){
      //kDist[i][where[adjncy[j]]] += 1.0*adjwgt[j]/w[i];
      linearTerm[ii][where[adjncy[j]]] += adjwgt[j];
      if (adjncy[j] == s)
	self_sim[ii] = adjwgt[j];
    }
  }
  
  //the diagonal entries won't affect the result so diagonal's assumed zero  
  obj =  0;
  for (i=0; i<nparts; i++)
    if (sum[i] >0)
      obj +=  squared_sum[i]*1.0/sum[i];

  srand(time(NULL));
  //temperature = DEFAULT_TEMP;
  loopTimes = 0;

  while (loopTimes < chain_length){
    accum_change =0;
    //for (j=0; j<nvtxs; j++)
    for (ii=0; ii<nbnd; ii++){
      minchange = onePoint_move(graph, nparts, sum, squared_sum, w, self_sim, linearTerm, ii);
      accum_change += minchange;
    }
    
    if (accum_change > -epsilon * obj){
      break;
    }
    moves ++; 
    loopTimes ++;
  } 

  free(sum); free(squared_sum); free(self_sim);
  
  //for (i= 0; i<nvtxs; i++)
  for (i= 0; i<nbnd; i++)
    free(linearTerm[i]);
  free(linearTerm);
  
  //printf("moves = %d\n", moves);
  return moves;
}


void remove_empty_clusters_l1(CtrlType *ctrl, GraphType *graph, int nparts, idxtype *w, float *tpwgts, float ubfactor){
  int *clustersize=imalloc(nparts, "remove_empty_clusters: clusterSize");
  int number_of_empty_cluster=0, i, s;

  for(i=0; i<nparts; i++)
    clustersize[i] =0;
  clusterSize(graph, clustersize);
  for(i=0; i<nparts; i++)
    if(clustersize[i] ==0)
      number_of_empty_cluster ++;
  
  if(number_of_empty_cluster>0)
    local_search(ctrl, graph, nparts, 1, w, tpwgts, ubfactor);
  
  free(clustersize);
}

void remove_empty_clusters_l2(CtrlType *ctrl, GraphType *graph, int nparts, idxtype *w, float *tpwgts, float ubfactor){
  int *clustersize=imalloc(nparts, "remove_empty_clusters: clusterSize");
  int number_of_empty_cluster=0, i, s;

  for(i=0; i<nparts; i++)
    clustersize[i] =0;
  clusterSize(graph, clustersize);
  for(i=0; i<nparts; i++)
    if(clustersize[i] ==0)
      number_of_empty_cluster ++;
  //printf("%d empty clusters; ", number_of_empty_cluster);

  if(number_of_empty_cluster>0){
    int nvtxs, me, j, k, ii;
    idxtype *sum, *squared_sum, *xadj, *adjncy, *adjwgt, *where, *bndptr, *bndind, *self_sim, nbnd;
    int **linearTerm;
    
    nvtxs = graph->nvtxs;
    xadj = graph->xadj;
    adjncy = graph->adjncy;
    adjwgt = graph->adjwgt;
    where = graph->where;
    nbnd = graph->nbnd;
    bndind = graph->bndind;
    bndptr = graph->bndptr;
    
    sum = idxsmalloc(nparts,0, "Local_search: weight sum");
    squared_sum = idxsmalloc(nparts,0,"Local_search: weight squared sum");
    self_sim = idxsmalloc(nbnd, 0, "Local_search: self similarity");
    linearTerm = i2malloc(nbnd, nparts, "Local_search: linear term");
    
    for (i=0; i<nvtxs; i++)
      sum[where[i]] += w[i]; 
    for (i=0; i<nvtxs; i++){
      me = where[i];
      for (j=xadj[i]; j<xadj[i+1]; j++) 
	if (where[adjncy[j]] == me)
	  squared_sum[me] += adjwgt[j];
    }
    
    for (ii = 0; ii<nbnd; ii++)
      for (j = 0; j<nparts; j++)
	linearTerm[ii][j] = 0;
    for (ii =0; ii<nbnd; ii++){
      s = bndind[ii];
      for (j=xadj[s]; j<xadj[s+1]; j++){
	linearTerm[ii][where[adjncy[j]]] += adjwgt[j];
	if (adjncy[j] == s)
	  self_sim[ii] = adjwgt[j];
      }
    }
    for(k=0; k<nparts; k++)
      if(clustersize[k] ==0){
	move1Point2EmptyCluster(graph, nparts, sum, squared_sum, w, self_sim, linearTerm, k);
      }
    free(sum); free(squared_sum); free(self_sim);
    
    //for (i= 0; i<nvtxs; i++)
    for (i= 0; i<nbnd; i++)
      free(linearTerm[i]);
    free(linearTerm);
  }
  /*
  for(i=0; i<nparts; i++)
    clustersize[i] =0;
  number_of_empty_cluster=0;
  clusterSize(graph, clustersize);
  for(i=0; i<nparts; i++)
    if(clustersize[i] ==0)
      number_of_empty_cluster ++;
  printf("%d empty clusters\n", number_of_empty_cluster);
  */
  free(clustersize);
}

void MLKKMRefine(CtrlType *ctrl, GraphType *orggraph, GraphType *graph, int nparts, int chain_length, float *tpwgts, float ubfactor)
{
  int i, nlevels, mustfree=0, temp_cl;
  GraphType *ptr;

  IFSET(ctrl->dbglvl, DBG_TIME, starttimer(ctrl->UncoarsenTmr));

  /* Compute the parameters of the coarsest graph */
  ComputeKWayPartitionParams(ctrl, graph, nparts);
  temp_cl = chain_length;

  /* Determine how many levels are there */
  for (ptr=graph, nlevels=0; ptr!=orggraph; ptr=ptr->finer, nlevels++); 
  //printf("Number of levels is %d\n", nlevels);

  for (i=0; ;i++) {
    timer tmr;
    float result;

    cleartimer(tmr);
    starttimer(tmr);
    
    //pingpong(ctrl, graph, nparts, chain_length, tpwgts, ubfactor);
    //chain_length /= 1.5;
    //printf("Level: %d\n", i+1);
    
    if (graph == orggraph){
      //chain_length = chain_length>0 ? chain_length : 1;
      pingpong(ctrl, graph, nparts, chain_length, tpwgts, ubfactor, 1);
      break;
    }
    else{
      //pingpong(ctrl, graph, nparts, 0, tpwgts, ubfactor, 0);
      pingpong(ctrl, graph, nparts, chain_length, tpwgts, ubfactor, 0);
      //chain_length /= 2;
    }
    
    
    //pingpong(ctrl, graph, nparts, chain_length, tpwgts, ubfactor);
    
    //    /* for time and quality each level 
    
    stoptimer(tmr);
    //printf("Level %d: %7.3f", i+1, tmr);
    if (cutType == NCUT){
      result = ComputeNCut(graph, graph->where, nparts);
      //printf("   %7f", result);
    }
    else{
      result = ComputeRAsso(graph, graph->where, nparts);
      //printf("   %7f", result);
    }
    //printf(" (%d)\n\n", graph->nvtxs);
    //ends here*/

    if (graph == orggraph)
      break;
    /*
    if(i>1)
      chain_length /= 10;
    */

    GKfree((void **) &graph->gdata, LTERM);  /* Deallocate the graph related arrays */
    graph = graph->finer;
    IFSET(ctrl->dbglvl, DBG_TIME, starttimer(ctrl->ProjectTmr));
    if (graph->vwgt == NULL) {
      graph->vwgt = idxsmalloc(graph->nvtxs, 1, "RefineKWay: graph->vwgt");
      graph->adjwgt = idxsmalloc(graph->nedges, 1, "RefineKWay: graph->adjwgt");
      mustfree = 1;
    }
    ProjectKWayPartition(ctrl, graph, nparts);
    IFSET(ctrl->dbglvl, DBG_TIME, stoptimer(ctrl->ProjectTmr));
  }
  
  if (mustfree) 
    GKfree((void **) &graph->vwgt, (void **) &graph->adjwgt, LTERM);

  IFSET(ctrl->dbglvl, DBG_TIME, stoptimer(ctrl->UncoarsenTmr));
}